Helvine-group minerals from Norwegian granitic pegmatites and some other granitic rocks: Cases of significant Sc and Sn contents
Bibliographic record
Abstract
ABSTRACT Helvine-group minerals from two granitic pegmatites have disparate compositions, from nearly pure helvine (Ågskardet, northern Norway; Devonian) to helvine close to ternary compositions (Heftetjern, southern Norway; Precambrian). Metagranite from Høgtuva (northern Norway; Precambrian with Caledonian metamorphic overprint) contains Zn-rich danalite. The Ågskardet helvine contains up to 0.46 wt.% SnO2, and the Heftetjern ternary helvine shows a maximum of 1.74 wt.% Sc2O3. Helvine minerals were also analyzed from three occurrences connected to peralkaline granite (ekerite) of the Permian Oslo Rift. Nearly pure genthelvite (99.19 mol.%) occurs in miarolitic cavities at Gjerdingselva. Two mineralogically different granitic pegmatites derived from the same ekerite pluton in the southern part of the Oslo Rift show quite distinct helvine compositions, from nearly continuous solid solution between helvine and genthelvite in crystals with oscillatory zonation (Rundemyr) to solid solutions midway between danalite and genthelvite (Bakstevalåsen). The Rundemyr crystals have a maximum SnO2 content of 1.28 wt.%. The incorporation of minor elements (Ca, Mg, Al, Sn, Sc) in helvine-group minerals is discussed with emphasis on their chalcophilicity characteristics. For stereochemical reasons, Sn in helvine minerals must be tetravalent, even if Sn2+ is more chalcophile than Sn4+.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".